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Sas Data Analyst Resume Profile

Summary

Information Technology professional with more than 22 years of SAS consulting, data analysis, statistical programming, database development, data modeling, data warehousing, healthcare informatics, systems analysis, and development and design of desktop and web applications. Also, more than 11 years of experience in medical claims fraud detection.

Career Skills /Knowledge:

  • Superior computer programming skills in SAS, SQL, C, Visual C , Visual Basic, ADO, ASP, Java, Javascripts, HTML, PHP, CSS style sheets, Unix Scripting, Objective-C
  • Superior statistical programming using: SAS, SAS Stats, Proc Mix, Proc GLM, Proc Univariate, Proc Report, Proc Tabulate, Data null, Proc Means, Proc Summary, Proc Freq, Proc Gchart, Proc Gmap, and SAS Macros
  • Superior ETL capabilities using: SAS, Teradata, DB2, SQL Server, MySql, MS Access, and Excel
  • Able to comprehend and utilize new technical information
  • Ability to demonstrate sensitivity in customer communications
  • Able to interface professionally with customers and peers
  • Excellent customer service skills and oral and written communication skills
  • Able to execute complex operational instructions, and job set-ups
  • Posses a thorough understanding of computer operations procedures, policies, tools and techniques

PROFESSIONAL EXPERIENCE

Confidential

SAS developer to conduct iterative, phased data analysis of a multiregional/national dataset including delivery system program and benchmark results based on various NCQA/HEDIS quality performance measures. Create analytical database from responses receive via on-line survey.

Confidential

  • Duties: Develop, test, implement and maintain program code to support Consumer Lending reporting, strategies and initiatives. Create and disseminate completed reports. Create and update project plans. Resolve minor issues and elevate unresolved issues as appropriate.
  • Collaborate with team members to share expertise and generate alternative solutions to project or environmental issues.
  • Gather business requirements for report and data file creation requests. Translate business requirements into technical specifications.
  • Consult with project lead and management regarding best practices. Provide regularly scheduled progress reports both to business partners and direct management.
  • Conduct code reviews and recommend alternative programming tools to improve quality and timeliness of results. Coordinate with Business Technology to monitor accuracy and timeliness of data. Prepare formal and informal communications to internal business partners and direct management regarding initiatives, issues, and achievements.

Confidential

22 years experience as a consultant. Worked on multiple projects for different healthcare and pharmaceutical companies simultaneously. Supported large clinical, administrative, and financial databases for analytics and report development. Developed numerous data mining and data management algorithms, report distribution systems, and customized software applications. Experienced in Data management, Data Warehousing, Database Development, ETL processes, System Design, Systems Analysis, Application and Web Development. Databases used: SAS, Teradata, Oracle, DB2, MySql, SQL Server, and MS Access. Operating systems used: Windows every version , Unix Solaris, HP-UX, AIX, Linux , and Mac.

Confidential

  • Use SAS programming and data analysis skills to extract, transform, translate, reformat, and load ETL raw healthcare data in HDMS's DART platform. Dart is a proprietary web based OLAP built around SAS, and Futrix. Developed Fieldstatus, and Autoread programs to speed up data scrubbing and data loading process.
  • Tools used: SAS, Excel, shell scripts. Operating system used: Unix, Windows.

Confidential

  • Provide analytical and data mining services related to the discovery and repayment of fraudulent Medicare and Medicaid claims. Algos: Inpatient After Death, Ventilator In Patient Facility, Acute to Acute Transfers, Duplicate Billing Same Provider, Duplicate Billing Different Provider, AfterHoursCodeAbuse, E M, and Unbundling SPSD to name a few. Also wrote ETL programs to extract data from Galaxy data warehouse for analysis, and extracted data from Americhoice SMART data warehouse to prepare for loading into PEERAnalysis.
  • Tools used: Oracle, DB2, SAS Systems, SAS EG, MS Excel. Operating system used: Windows, Solaris.

Confidential

  • Provide analytical services related to assessing the potential impact of enrolling California's disabled, non-dual eligible Medicaid population in an Enhanced Primary Care Case Management EPCCM program. Also, provide analytical services related to disease management and also FQHC claims fraud. Data and statistical analysis performed using SAS and SQL.
  • Tools used: DB2, SAS Systems, MS Access, and MS Excel. Operating system used: Windows.

Confidential

  • Contract awarded after submitting winning proposal. Developed data mining algorithms to detect Medicaid/Medicare claims fraud. Helped Illinois HFS to save tens of millions of dollars in fraudulent Medicaid claims. Developed data mining algorithms to discover, extract, and transform data to report and support the following investigations:
  • Payment Accuracy Review and Random Claims Sampling, Day Training, Duplicate Transportation Services, Duplicate Radiology, DRG Self Audit, Hospital Transfers, Inpatient Services, Inpatient Lab Services, Inpatient Pharmacy, Inpatient Transportation, Inpatient DRG, Long Term Care Stay, Time Dependent Billing and the Medi-Medi project.
  • Tools used: TeraData Database Server, SAS Systems, SAS EG and SAS BI, MS Access, MS Excel, BI/Query and QueryMan. Operating system used: Windows/ NT / 2000.

Confidential

  • Consultant to Outcomes Research and Data Management departments. Wrote algorithms to improve DM's ETL processes and organize baseline, reconciliation, and outcomes data into reporting tables to improve overall reporting capabilities. Analyze and evaluate client data, develop data cleaning applications to recover corrupt data.
  • Tools used: SAS, SQL Server, MS Access, and MS Excel.

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